Model-based analysis of ChIP-Seq (MACS)

Academic Article

Abstract

  • We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available. © 2008 Zhang et al.; licensee BioMed Central Ltd.
  • Digital Object Identifier (doi)

    Author List

  • Zhang Y; Liu T; Meyer CA; Eeckhoute J; Johnson DS; Bernstein BE; Nussbaum C; Myers RM; Brown M; Li W
  • Volume

  • 9
  • Issue

  • 9